Monte Carlo simulation is widely used to numerically solve stochastic differential equations. Although the method is flexible and easy to implement, it may be slow to converge. Moreover, an inaccurate solution will result when using large time steps. The Seven League scheme, a deep learning-based numerical method, has been proposed to address these issues. This paper generalizes the scheme regarding parallel computing, particularly on Graphics Processing Units (GPUs), improving the computational speed.

翻译：Monte Carlo模拟在数字上广泛用于解决随机差分方程式。 虽然该方法灵活易行,但趋同速度可能较慢。 此外,使用大型时间步骤将会产生不准确的解决方案。 为了解决这些问题,已提议采用基于深层学习的数值方法“七联计划 ” 。本文概括了平行计算,特别是图形处理器(GPUs)的平行计算方法,以提高计算速度。